{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/Qa.png.\r\n",
      "  + Squared l2 distance between representations: 0.184\r\n"
     ]
    }
   ],
   "source": [
    "!/root/openface/demos/compare.py /mnt/data/wangli/test_img/Q1.jpg /mnt/data/wangli/test_img/Qa.png"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing /mnt/data/wangli/test_img/Qa.png with /mnt/data/wangli/test_img/Y2.jpg.\r\n",
      "  + Squared l2 distance between representations: 0.499\r\n"
     ]
    }
   ],
   "source": [
    "!/root/openface/demos/compare.py /mnt/data/wangli/test_img/Qa.png /mnt/data/wangli/test_img/Y2.jpg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/F4.jpg.\r\n",
      "  + Squared l2 distance between representations: 0.168\r\n"
     ]
    }
   ],
   "source": [
    "!/root/openface/demos/compare.py /mnt/data/wangli/test_img/Q1.jpg /mnt/data/wangli/test_img/F4.jpg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing /mnt/data/mydataset/test_img/tock15.jpg with /mnt/data/mydataset/test_img/tock16.jpg.\r\n",
      "  + Squared l2 distance between representations: 0.057\r\n"
     ]
    }
   ],
   "source": [
    "!/root/openface/demos/compare.py /mnt/data/mydataset/test_img/Q1.jpg /mnt/data/mydataset/test_img/Q2.jpg "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一比一的识别上 任然有很高的误识率 ， F4和Q1 Q4 Qa 就比较相似的结果 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/C3.jpg.\n",
      "  + Squared l2 distance between representations: 0.545\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/F4.jpg.\n",
      "  + Squared l2 distance between representations: 0.521\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/H4.jpg.\n",
      "  + Squared l2 distance between representations: 0.419\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/Q1.jpg.\n",
      "  + Squared l2 distance between representations: 0.358\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/Q2.jpg.\n",
      "  + Squared l2 distance between representations: 0.324\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/Q3.jpg.\n",
      "  + Squared l2 distance between representations: 0.608\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/Q4.jpg.\n",
      "  + Squared l2 distance between representations: 0.389\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/Q5.jpg.\n",
      "  + Squared l2 distance between representations: 1.001\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.644\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.516\n",
      "Comparing /mnt/data/wangli/test_img/A2.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.568\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/F4.jpg.\n",
      "  + Squared l2 distance between representations: 0.539\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/H4.jpg.\n",
      "  + Squared l2 distance between representations: 0.358\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/Q1.jpg.\n",
      "  + Squared l2 distance between representations: 0.595\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/Q2.jpg.\n",
      "  + Squared l2 distance between representations: 0.558\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/Q3.jpg.\n",
      "  + Squared l2 distance between representations: 0.800\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/Q4.jpg.\n",
      "  + Squared l2 distance between representations: 0.668\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/Q5.jpg.\n",
      "  + Squared l2 distance between representations: 0.846\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.831\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.524\n",
      "Comparing /mnt/data/wangli/test_img/C3.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.829\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/H4.jpg.\n",
      "  + Squared l2 distance between representations: 0.437\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/Q1.jpg.\n",
      "  + Squared l2 distance between representations: 0.168\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/Q2.jpg.\n",
      "  + Squared l2 distance between representations: 0.166\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/Q3.jpg.\n",
      "  + Squared l2 distance between representations: 0.266\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/Q4.jpg.\n",
      "  + Squared l2 distance between representations: 0.162\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/Q5.jpg.\n",
      "  + Squared l2 distance between representations: 0.666\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.385\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.145\n",
      "Comparing /mnt/data/wangli/test_img/F4.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.417\n",
      "Comparing /mnt/data/wangli/test_img/H4.jpg with /mnt/data/wangli/test_img/Q1.jpg.\n",
      "  + Squared l2 distance between representations: 0.450\n",
      "Comparing /mnt/data/wangli/test_img/H4.jpg with /mnt/data/wangli/test_img/Q2.jpg.\n",
      "  + Squared l2 distance between representations: 0.447\n",
      "Comparing /mnt/data/wangli/test_img/H4.jpg with /mnt/data/wangli/test_img/Q3.jpg.\n",
      "  + Squared l2 distance between representations: 0.689\n",
      "Comparing /mnt/data/wangli/test_img/H4.jpg with /mnt/data/wangli/test_img/Q4.jpg.\n",
      "  + Squared l2 distance between representations: 0.442\n",
      "Comparing /mnt/data/wangli/test_img/H4.jpg with /mnt/data/wangli/test_img/Q5.jpg.\n",
      "  + Squared l2 distance between representations: 0.651\n",
      "Comparing /mnt/data/wangli/test_img/H4.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.800\n",
      "Comparing /mnt/data/wangli/test_img/H4.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.353\n",
      "Comparing /mnt/data/wangli/test_img/H4.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.753\n",
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/Q2.jpg.\n",
      "  + Squared l2 distance between representations: 0.027\n",
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/Q3.jpg.\n",
      "  + Squared l2 distance between representations: 0.180\n",
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/Q4.jpg.\n",
      "  + Squared l2 distance between representations: 0.078\n",
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/Q5.jpg.\n",
      "  + Squared l2 distance between representations: 0.684\n",
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.272\n",
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.184\n",
      "Comparing /mnt/data/wangli/test_img/Q1.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.373\n",
      "Comparing /mnt/data/wangli/test_img/Q2.jpg with /mnt/data/wangli/test_img/Q3.jpg.\n",
      "  + Squared l2 distance between representations: 0.269\n",
      "Comparing /mnt/data/wangli/test_img/Q2.jpg with /mnt/data/wangli/test_img/Q4.jpg.\n",
      "  + Squared l2 distance between representations: 0.051\n",
      "Comparing /mnt/data/wangli/test_img/Q2.jpg with /mnt/data/wangli/test_img/Q5.jpg.\n",
      "  + Squared l2 distance between representations: 0.745\n",
      "Comparing /mnt/data/wangli/test_img/Q2.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.353\n",
      "Comparing /mnt/data/wangli/test_img/Q2.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.179\n",
      "Comparing /mnt/data/wangli/test_img/Q2.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.376\n",
      "Comparing /mnt/data/wangli/test_img/Q3.jpg with /mnt/data/wangli/test_img/Q4.jpg.\n",
      "  + Squared l2 distance between representations: 0.324\n",
      "Comparing /mnt/data/wangli/test_img/Q3.jpg with /mnt/data/wangli/test_img/Q5.jpg.\n",
      "  + Squared l2 distance between representations: 0.582\n",
      "Comparing /mnt/data/wangli/test_img/Q3.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.124\n",
      "Comparing /mnt/data/wangli/test_img/Q3.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.376\n",
      "Comparing /mnt/data/wangli/test_img/Q3.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.410\n",
      "Comparing /mnt/data/wangli/test_img/Q4.jpg with /mnt/data/wangli/test_img/Q5.jpg.\n",
      "  + Squared l2 distance between representations: 0.773\n",
      "Comparing /mnt/data/wangli/test_img/Q4.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.410\n",
      "Comparing /mnt/data/wangli/test_img/Q4.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.178\n",
      "Comparing /mnt/data/wangli/test_img/Q4.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.369\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing /mnt/data/wangli/test_img/Q5.jpg with /mnt/data/wangli/test_img/Q6.jpg.\n",
      "  + Squared l2 distance between representations: 0.623\n",
      "Comparing /mnt/data/wangli/test_img/Q5.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.634\n",
      "Comparing /mnt/data/wangli/test_img/Q5.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.680\n",
      "Comparing /mnt/data/wangli/test_img/Q6.jpg with /mnt/data/wangli/test_img/Qa.png.\n",
      "  + Squared l2 distance between representations: 0.481\n",
      "Comparing /mnt/data/wangli/test_img/Q6.jpg with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.571\n",
      "Comparing /mnt/data/wangli/test_img/Qa.png with /mnt/data/wangli/test_img/Y2.jpg.\n",
      "  + Squared l2 distance between representations: 0.499\n"
     ]
    }
   ],
   "source": [
    "!/root/openface/demos/compare.py /mnt/data/wangli/test_img/*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    " \n",
    "import matplotlib.pyplot as plt \n",
    "\n",
    "%matplotlib inline \n",
    "import os\n",
    "import matplotlib.image as mpimg # mpimg 用于读取图片"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f52b5bfba20>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#y显示原图\n",
    "image1=os.path.normpath(\"/mnt/data/mydataset/test_img/H3.jpg\")\n",
    "im = mpimg.imread(image1)  ##文件存在的路径\n",
    "plt.imshow(im)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# dlib 特征提取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "import openface\n",
    "\n",
    "\n",
    "modelDir = os.path.join('/root/openface', 'models')\n",
    "dlibModelDir = os.path.join(modelDir, 'dlib')\n",
    "openfaceModelDir = os.path.join(modelDir, 'openface')\n",
    "\n",
    "dlibFacePredictor=os.path.join(dlibModelDir, \"shape_predictor_68_face_landmarks.dat\")\n",
    "align = openface.AlignDlib(dlibFacePredictor)\n",
    "\n",
    "networkModel=os.path.join(openfaceModelDir, 'nn4.small2.v1.t7')\n",
    "\n",
    "imgDim=96\n",
    "net = openface.TorchNeuralNet(networkModel, imgDim, cuda=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 参数说明\n",
    "### bb=getLargestFaceBoundingBox 获取 人脸位置 dlib对象\n",
    "可以使用dlib 的类方法 获取上下左右坐标 长宽面积等等\n",
    "\n",
    "###  alignedFace   rgb图片，numarray type\n",
    "\n",
    "### rep1 特征向量  Vector of features extracted with the neural network.\n",
    "这里 神经网络 所关注的特征位置在哪里？ 这是需要关心的，一次确定模型的可靠性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[177 113  91]\n",
      "  [184 120  95]\n",
      "  [188 123  94]\n",
      "  ...\n",
      "  [193 124  86]\n",
      "  [169 108  68]\n",
      "  [154 100  61]]\n",
      "\n",
      " [[225 154 129]\n",
      "  [226 155 130]\n",
      "  [217 145 117]\n",
      "  ...\n",
      "  [186 114  74]\n",
      "  [180 118  81]\n",
      "  [201 147 111]]\n",
      "\n",
      " [[234 157 130]\n",
      "  [231 153 126]\n",
      "  [233 153 126]\n",
      "  ...\n",
      "  [194 115  76]\n",
      "  [185 108  70]\n",
      "  [223 147 111]]\n",
      "\n",
      " ...\n",
      "\n",
      " [[199 179 178]\n",
      "  [202 182 184]\n",
      "  [207 187 189]\n",
      "  ...\n",
      "  [203 184 186]\n",
      "  [196 173 183]\n",
      "  [193 170 178]]\n",
      "\n",
      " [[196 176 175]\n",
      "  [201 181 183]\n",
      "  [206 186 188]\n",
      "  ...\n",
      "  [205 186 189]\n",
      "  [199 176 186]\n",
      "  [196 173 182]]\n",
      "\n",
      " [[195 175 175]\n",
      "  [200 180 182]\n",
      "  [206 186 188]\n",
      "  ...\n",
      "  [207 190 196]\n",
      "  [202 183 187]\n",
      "  [197 178 182]]]\n",
      "[-0.04823682  0.18742916  0.10349771  0.01622758 -0.07920825  0.18418182\n",
      " -0.04755501  0.11765502 -0.03806997 -0.00565012  0.01777929 -0.01703\n",
      " -0.00539334 -0.19718678 -0.02624744 -0.01370947 -0.14151733  0.0444403\n",
      " -0.03443312 -0.10042656  0.17812212 -0.04376784  0.04098167 -0.05810674\n",
      "  0.07003534 -0.14154942 -0.05308048 -0.1047777  -0.03116136  0.02980629\n",
      "  0.05420141 -0.1885093   0.02498628  0.03897895  0.05643936 -0.0853827\n",
      "  0.00085733 -0.0606497   0.02975015  0.04396465 -0.03279868 -0.09614088\n",
      "  0.07344153  0.04059146 -0.02388976 -0.14717957  0.1186996  -0.15192969\n",
      " -0.14261861  0.08606173  0.13423577  0.00966114 -0.07915296  0.09458911\n",
      " -0.02650916  0.04425854  0.09369011 -0.12739037 -0.00600445 -0.1416897\n",
      " -0.00761181 -0.05696612 -0.01379499 -0.12155714  0.09963537 -0.12398237\n",
      " -0.00090877 -0.0621035  -0.0725146   0.10524599  0.04705767  0.06396072\n",
      " -0.0573702  -0.09163212  0.01246587  0.04448748 -0.06296874  0.03897114\n",
      " -0.01047092  0.11572486 -0.14984345 -0.07062834  0.1430366   0.18275116\n",
      " -0.06022245  0.11825877  0.02632275 -0.02961387  0.05329793 -0.00269758\n",
      " -0.1384427  -0.16615629 -0.07317352  0.00062159 -0.09433486 -0.08786668\n",
      " -0.02790975  0.13492781 -0.13300101  0.09976874 -0.012969    0.0883262\n",
      " -0.03131032  0.05810301  0.11441571  0.01326209  0.03961639  0.10416542\n",
      " -0.08161458 -0.06679596 -0.13024566 -0.09734808 -0.05161337 -0.01645465\n",
      "  0.04736932  0.04857118  0.00490309  0.04327077  0.04466372  0.08059722\n",
      "  0.02251338 -0.02501681 -0.0069314  -0.04963656  0.18189585 -0.0007312\n",
      "  0.17397241  0.12465493]\n",
      "[(349, 528) (617, 795)]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bb = align.getLargestFaceBoundingBox(im)\n",
    "alignedFace = align.align(imgDim, im, bb,\n",
    "                          landmarkIndices=openface.AlignDlib.OUTER_EYES_AND_NOSE)\n",
    "rep1 = net.forward(alignedFace)\n",
    "\n",
    "plt.imshow(alignedFace)\n",
    "# `rep2` obtained similarly.\n",
    "print(alignedFace)\n",
    "print(rep1)\n",
    "print(bb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 准确率的影响因素\n",
    "* 图片质量\n",
    "\n",
    "|pixels | val- rate |\n",
    "|-|-|\n",
    "|1600|37.8%|\n",
    "|6400|79.5%|\n",
    "|14400|84.5%|\n",
    "|25600|85.7%|\n",
    "|65536|56.4%|\n",
    "\n",
    "这就表示了  在实际街景中 需要的摄像头分辨率 和安装距离  是有固定范围的\n",
    "___\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "##  框出人脸位置\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'faceRectWidth': 269, 'faceRectHeight': 268, 'faceRectPoint': (349, 528)}\n",
      "<class 'dlib.rectangle'>\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "import matplotlib.patches as patches\n",
    "plt.figure(8)\n",
    "plt.imshow(im)\n",
    "currentAxis=plt.gca()\n",
    "\n",
    "faceRect={\"faceRectWidth\":bb.width(),\"faceRectHeight\":bb.height(),\"faceRectPoint\":(bb.left(),bb.top())}\n",
    "rect=patches.Rectangle(faceRect[\"faceRectPoint\"],faceRect[\"faceRectWidth\"],faceRect[\"faceRectHeight\"],linewidth=1,edgecolor='r',facecolor='none')\n",
    "currentAxis.add_patch(rect)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "print(faceRect)\n",
    "print(type(bb))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 特征降维 与可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Note: This example assumes that `name i` corresponds to `label i`\n",
      "in `labels.csv`.\n",
      "\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/root/openface/util/tsne.py\", line 47, in <module>\n",
      "    plt.savefig(out)\n",
      "  File \"/usr/local/lib/python2.7/dist-packages/matplotlib/pyplot.py\", line 577, in savefig\n",
      "    res = fig.savefig(*args, **kwargs)\n",
      "  File \"/usr/local/lib/python2.7/dist-packages/matplotlib/figure.py\", line 1476, in savefig\n",
      "    self.canvas.print_figure(*args, **kwargs)\n",
      "  File \"/usr/local/lib/python2.7/dist-packages/matplotlib/backend_bases.py\", line 2211, in print_figure\n",
      "    **kwargs)\n",
      "  File \"/usr/local/lib/python2.7/dist-packages/matplotlib/backends/backend_pdf.py\", line 2477, in print_pdf\n",
      "    file = PdfFile(filename)\n",
      "  File \"/usr/local/lib/python2.7/dist-packages/matplotlib/backends/backend_pdf.py\", line 418, in __init__\n",
      "    fh = open(filename, 'wb')\n",
      "IOError: [Errno 16] Device or resource busy: '/mnt//tsne.pdf'\n"
     ]
    }
   ],
   "source": [
    "! /root/openface/util/tsne.py  /mnt/ --names 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 从训练的128d 向量看 样本少的个人 与其他个人重合的机会很大\n",
    "<img src = \"./doc/tsne.png\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
